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This project will evaluate the effects of a technology-based patient-reported outcomes system on patient management of type 2 diabetes in primary care practices.
This project will adapt and evaluate a mobile health application to improve patient-reported asthma outcomes in New York.
This research prospectively evaluated a machine learning algorithm that identifies candidates for neurologic surgery to control epilepsy.
This project will analyze and model the information requirements, decisionmaking, and workflow of homecare nurses admitting patients and characterize if and how health information technology systems support their needs.
This project designed and conducted a usability evaluation of dashboards that provide feedback to home care nurses to improve the care of patients with chronic heart failure, and found that the dashboard prototype had high usability and was evaluated positively by users.
This study aimed to improve care transitions for low-income patients with multiple chronic conditions using health information exchange, and found significant reductions in inpatient and emergency department utilization.
Evaluated the effects of a Web portal-based patient empowerment program and EMR system on quality of care, patient safety, and utilization for patients with diabetes and physicians in primary care practices.